Using drawdata to generate fake data
Creating machine learning models helps in understanding the interaction between different columns/data points. It shows us how we can calculate the deviation a data point shows with respect to change in the feature data points.
While learning data science, generally everyone starts learning using the dataset that is already there in the sklearn and is used for ages, but in order to get a better understanding of data correlation and how data behaves in different machine learning models, we need more datasets.
Drawdata is an open-source python library that helps in generating data by just drawing it out. It allows users to create diverse datasets with different shapes which can help in learning data science/machine learning.
In this article, we will be exploring different techniques to generate data using drawdata. Let’s get started…!
Installing required libraries
We will start by installing the drawdata using pip. The command given below will do that.
python -m pip install drawdata
Importing required libraries
In this step, we will import the required libraries which will help us in generating data using different techniques.
from drawdata import draw_line, draw_scatter, draw_histogram
Now we will be creating datasets and also download them using a GUI created by drawdata.
- Using Scatter Tool
Here we can clearly see how it creates a GUI where we can create different data points and also download the dataset in different formats.
2. Using Line Tool
3. Using Histogram Tool
This is how we can create different datasets using drawdata and download the datasets to create a machine learning model. Go ahead try this and create different datasets to learn machine learning/data science. Please let me know your comments in the response section.
This article is in collaboration with Piyush Ingale.
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